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Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)

Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no informati...

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Autores principales: Kunze, Nils, Göpel, Julia, Kuhns, Martin, Jünger, Melanie, Quintel, Michael, Perl, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer-Verlag 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616217/
https://www.ncbi.nlm.nih.gov/pubmed/23467822
http://dx.doi.org/10.1007/s00253-013-4762-8
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author Kunze, Nils
Göpel, Julia
Kuhns, Martin
Jünger, Melanie
Quintel, Michael
Perl, Thorsten
author_facet Kunze, Nils
Göpel, Julia
Kuhns, Martin
Jünger, Melanie
Quintel, Michael
Perl, Thorsten
author_sort Kunze, Nils
collection PubMed
description Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species.
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spelling pubmed-36162172013-04-04 Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS) Kunze, Nils Göpel, Julia Kuhns, Martin Jünger, Melanie Quintel, Michael Perl, Thorsten Appl Microbiol Biotechnol Methods and Protocols Headspace analyses over microbial cultures using multi-capillary column-ion mobility spectrometry (MCC-IMS) could lead to a faster, safe and cost-effective method for the identification of pathogens. Recent studies have shown that MCC-IMS allows identification of bacteria and fungi, but no information is available from when on during their growth a differentiation between bacteria is possible. Therefore, we analysed the headspace over human pathogenic reference strains of Escherichia coli and Pseudomonas aeruginosa at four time points during their growth in a complex fluid medium. In order to validate our findings and to answer the question if the results of one bacterial strain can be transferred to other strains of the same species, we also analysed the headspace over cultures from isolates of random clinical origin. We detected 19 different volatile organic compounds (VOCs) that appeared or changed their signal intensity during bacterial growth. These included six VOCs exclusively changing over E. coli cultures and seven exclusively changing over P. aeruginosa cultures. Most changes occurred in the late logarithmic or static growth phases. We did not find differences in timing or trends in signal intensity between VOC patterns of different strains of one species. Our results show that differentiation of human pathogenic bacteria by headspace analyses using MCC-IMS technology is best possible during the late phases of bacterial growth. Our findings also show that VOC patterns of a bacterial strain can be transferred to other strains of the same species. Springer-Verlag 2013-03-07 2013 /pmc/articles/PMC3616217/ /pubmed/23467822 http://dx.doi.org/10.1007/s00253-013-4762-8 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by-nc/2.0/ Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
spellingShingle Methods and Protocols
Kunze, Nils
Göpel, Julia
Kuhns, Martin
Jünger, Melanie
Quintel, Michael
Perl, Thorsten
Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title_full Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title_fullStr Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title_full_unstemmed Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title_short Detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (MCC-IMS)
title_sort detection and validation of volatile metabolic patterns over different strains of two human pathogenic bacteria during their growth in a complex medium using multi-capillary column-ion mobility spectrometry (mcc-ims)
topic Methods and Protocols
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3616217/
https://www.ncbi.nlm.nih.gov/pubmed/23467822
http://dx.doi.org/10.1007/s00253-013-4762-8
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